15 June 2017 Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography
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Abstract
The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm’s canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC’s was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Alex S. Huang, Alex S. Huang, Akram Belghith, Akram Belghith, Anna Dastiridou, Anna Dastiridou, Vikas Chopra, Vikas Chopra, Linda M. Zangwill, Linda M. Zangwill, Robert N. Weinreb, Robert N. Weinreb, } "Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography," Journal of Biomedical Optics 22(6), 066010 (15 June 2017). https://doi.org/10.1117/1.JBO.22.6.066010 . Submission: Received: 6 January 2017; Accepted: 30 May 2017
Received: 6 January 2017; Accepted: 30 May 2017; Published: 15 June 2017
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